Immunological responses and cytokine gene expression analysis to Cooperia punctata infections in resistant and susceptible Nelore cattle

Cellular and humoral immune response, as well as cytokine gene expression, was assessed in Nelore cattle with different degrees of resistance to Cooperia punctata natural infection. One hundred cattle (male, weaned, 11-12 months old), kept together on pasture, were evaluated. Faecal and blood samples were collected for parasitological and immunological assays. Based on nematode faecal egg counts (FEC) and worm burden, the seven most resistant and the eight most susceptible animals were selected. Tissue samples of the small intestine were collected for histological quantification of inflammatory cells and analysis of cytokine gene expression (IL-2, IL-4, IL-8, IL-1 2p35, IL-13, TNF-alpha, IFN-gamma, MCP-1, MCP-2, and MUC- 1) using real-time RT-PCR. Mucus samples were also collected for IgA levels determination. Serum IgG1 mean levels against C. punctata antigens were higher in the resistant group, but significant differences between groups were only observed 14 days after the beginning of the experiment against infective larvae (1-3) and 14 and 84 days against adult antigens. The resistant group also presented higher IgA levels against C. punctata (L3 and adult) antigens with significant difference 14 days after the beginning of the trial (P < 0.05). In the small-intestine mucosa, levels of IgA anti-L3 and anti-adult C. punctata were higher in the resistant group, compared with the susceptible group (P < 0.05). Gene expression of both T(H)2 cytokines (IL-4 and IL-13) in the resistant group and T(H)1 cytokines (IL-2, IL-1 2p35, IFN-gamma and MCP-1) in the susceptible group was up-regulated. Such results suggested that immune response to C. punctata was probably mediated by TH2 cytokines in the resistant group and by T(H)1 cytokines in the susceptible group. (C) 2008 Elsevier B.V. All rights reserved.

Application of rotor response analysis to fault detection in hydro powerplants.

In this article some considerations obtained during the utilization of rotor response analysis techniques in hydraulic powerplants are discussed. An applied research work was carried out in two hydraulic turbines analysing the rotor response both theoretically and experimentally. A developed mathematical model was used to simulate the rotordynamic behaviour of Francis and Kaplan turbines. The main dynamical effects that appear during the operation of the machines are discussed too. A series of measurements were carried out in the turbines using impact hammers to determine the modal behaviour of the units. The tests were carried out with the machine still and in operation. Some results and the comparison with the theory is presented in this article. The improved theoretical model was used for a sensitivity analysis of the different bearings to the main excitations that fake place during the machine operation. From this analysis, the best measuring points for condition monitoring were determined.

Application of dissociation curve analysis to radiation hybrid panel marker scoring: generation of a map of river buffalo (B-bubalis) chromosome 20

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Tm-afm nonlinear motion control with robustness analysis to parametric errors in the control signal determination

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Why is it so difficult to identify a single indicator of water stress in plants? A proposal for a multivariate analysis to assess emergent properties

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Comparison of different methods of erythrocyte dysmorphism analysis to determine the origin of hematuria

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Using SPE-LC-ESI-MS/MS analysis to assess disperse dyes in environmental water samples

We have optimized an SPE-LC-ESI-MS/MS method and used it to monitor disperse azo dyes in environmental aquatic samples. Calibration curves constructed for nine disperse dyes-Red 1, Violet 93, Blue 373, Orange 1, Orange 3, Orange 25, Yellow 3, Yellow 7 and Red 13-in aqueous solution presented good linearity between 2.0 and 100.0 ng mL(-1). The method provided limits of detection and quantification around 2.0 and 8.0 ng L(-1), respectively. For dyes at concentrations of 25.0 ng mL(-1), the intra- and interday analyses afforded relative standard deviation lower than 6 and 13%, respectively. The recovery values obtained for each target analyte in Milli-Q water, receiving waters and treated water samples spiked with the nine studied dyes at concentrations of 8.0, 25.0 and 50.0 ng L(-1) (n = 3) gave average recoveries greater than 70%, with RSD <20%. Statistical evaluation aided method validation. The validated method proved to be useful for analysis of organic extracts from effluents and receiving water samples after an SPE extraction step. More specifically, the method enabled detection of the dyes Disperse Red 1, Disperse Blue 373 and Disperse Violet 93 at concentrations ranging from 84 to 3452 ng L(-1) in the treated effluent (TE), affluent and points collected upstream and downstream of the drinking water treatment plant of a textile dye industry in Brazil.

Using Source-Code Analysis to Help End-user Programmers Create Dependable Software

Not long ago, most software was written by professional programmers, who could be presumed to have an interest in software engineering methodologies and in tools and techniques for improving software dependability. Today, however, a great deal of software is written not by professionals but by end-users, who create applications such as multimedia simulations, dynamic web pages, and spreadsheets. Applications such as these are often used to guide important decisions or aid in important tasks, and it is important that they be sufficiently dependable, but evidence shows that they frequently are not. For example, studies have shown that a large percentage of the spreadsheets created by end-users contain faults. Despite such evidence, until recently, relatively little research had been done to help end-users create more dependable software. We have been working to address this problem by finding ways to provide at least some of the benefits of formal software engineering techniques to end-user programmers. In this talk, focusing on the spreadsheet application paradigm, I present several of our approaches, focusing on methodologies that utilize source-code-analysis techniques to help end-users build more dependable spreadsheets. Behind the scenes, our methodologies use static analyses such as dataflow analysis and slicing, together with dynamic analyses such as execution monitoring, to support user tasks such as validation and fault localization. I show how, to accommodate the user base of spreadsheet languages, an interface to these methodologies can be provided in a manner that does not require an understanding of the theory behind the analyses, yet supports the interactive, incremental process by which spreadsheets are created. Finally, I present empirical results gathered in the use of our methodologies that highlight several costs and benefits trade-offs, and many opportunities for future work.

Using AMS combined with mineral shape preferred orientation analysis to understand the emplacement fabrics of the Apiai gabbro-norite (Ribeira Belt, SE Brazil)

The Apiai gabbro-norite is a massive fine-grained Neoproterozoic intrusion emplaced in a core of synformal structure that deforms low-grade marine metasedimentary rocks of the Ribeira Belt of south-eastern Brazil. The lack of visible magmatic layering or any internal fabric has been a major limitation in deciding whether the emplacement occurred before or after the regional folding. To assist in the tectonic interpretations, we combine low-field anisotropy of magnetic susceptibility (AMS) and silicate shape preferred orientation (SPO) to reveal the internal structure of the mafic intrusion. Magnetic data indicate a mean susceptibility of about 10(-2) SI and a mean anisotropy degree (P) of about 1.08, essentially yielded by titanomagnetite. The magnetic and silicate foliations for P >= 1.10 are parallel to each other, while the lineations tend to scatter on the foliation plane, in agreement with the dominant oblate symmetry of the AMS and SPO ellipsoids. For lower P values, the magnetic and silicate fabrics vary from coaxial to oblique, and for P <= 1.05, their shapes and orientations can be quite distinct. The crystal size distribution (CSD) of plagioclase for P > 1.05 is log linear, in agreement with a bulk simple crystallisation history. These results combined show that for a strong SPO, corresponding to a magnetic anisotropy above 1.10, AMS is a reliable indicator of the magmatic fabric. They indicate that the Apiai gabbro-norite consists of sill-like body that was inclined gently to the north by the regional folding.

X-Ray analysis to assess mechanical damage in sweet corn seeds

The X-ray test is a precise, fast and non-destructive method to detect mechanical damage in seeds. In the present study, the efficiency of X-ray analysis in identifying the extent of mechanical damage in sweet corn seeds and its relationship with germination and vigor was evaluated. Hybrid 'SWB 551' (sh2) seeds with round (R) and flat (F) shapes were classified as large (L), medium (M1, M2 and M3) and small (S), using sieves with round and oblong screens. After artificial exposure to different levels of damage (0, 1, 3, 5 and 7 impacts), seeds were X-rayed (15 kV, 5 min) and submitted to germination (25 °C/5 days) and cold (10 °C/7 days) tests. Digital images of normal and abnormal seedlings and ungerminated seeds from germination and cold tests were jointly analyzed with the seed X-ray images. Results showed that damage affecting the embryonic axis resulted in abnormal seedlings or dead seeds in the germination and cold tests. The X-ray analysis is efficient for identifying mechanical damage in sweet corn seeds, allowing damage severity to be associated with losses in germination and vigor.

Perceived neighborhood problems: multilevel analysis to evaluate psychometric properties in a Southern adult Brazilian population

Abstract Background Physical attributes of the places in which people live, as well as their perceptions of them, may be important health determinants. The perception of place in which people dwell may impact on individual health and may be a more telling indicator for individual health than objective neighborhood characteristics. This paper aims to evaluate psychometric and ecometric properties of a scale on the perceptions of neighborhood problems in adults from Florianopolis, Southern Brazil. Methods Individual, census tract level (per capita monthly familiar income) and neighborhood problems perception (physical and social disorders) variables were investigated. Multilevel models (items nested within persons, persons nested within neighborhoods) were run to assess ecometric properties of variables assessing neighborhood problems. Results The response rate was 85.3%, (1,720 adults). Participants were distributed in 63 census tracts. Two scales were identified using 16 items: Physical Problems and Social Disorder. The ecometric properties of the scales satisfactory: 0.24 to 0.28 for the intra-class correlation and 0.94 to 0.96 for reliability. Higher values on the scales of problems in the physical and social domains were associated with younger age, more length of time residing in the same neighborhood and lower census tract income level. Conclusions The findings support the usefulness of these scales to measure physical and social disorder problems in neighborhoods.

A partial dependence factorial analysis to deal with selection bias in observational studis

This thesis presents a creative and practical approach to dealing with the problem of selection bias. Selection bias may be the most important vexing problem in program evaluation or in any line of research that attempts to assert causality. Some of the greatest minds in economics and statistics have scrutinized the problem of selection bias, with the resulting approaches – Rubin’s Potential Outcome Approach(Rosenbaum and Rubin,1983; Rubin, 1991,2001,2004) or Heckman’s Selection model (Heckman, 1979) – being widely accepted and used as the best fixes. These solutions to the bias that arises in particular from self selection are imperfect, and many researchers, when feasible, reserve their strongest causal inference for data from experimental rather than observational studies. The innovative aspect of this thesis is to propose a data transformation that allows measuring and testing in an automatic and multivariate way the presence of selection bias. The approach involves the construction of a multi-dimensional conditional space of the X matrix in which the bias associated with the treatment assignment has been eliminated. Specifically, we propose the use of a partial dependence analysis of the X-space as a tool for investigating the dependence relationship between a set of observable pre-treatment categorical covariates X and a treatment indicator variable T, in order to obtain a measure of bias according to their dependence structure. The measure of selection bias is then expressed in terms of inertia due to the dependence between X and T that has been eliminated. Given the measure of selection bias, we propose a multivariate test of imbalance in order to check if the detected bias is significant, by using the asymptotical distribution of inertia due to T (Estadella et al. 2005) , and by preserving the multivariate nature of data. Further, we propose the use of a clustering procedure as a tool to find groups of comparable units on which estimate local causal effects, and the use of the multivariate test of imbalance as a stopping rule in choosing the best cluster solution set. The method is non parametric, it does not call for modeling the data, based on some underlying theory or assumption about the selection process, but instead it calls for using the existing variability within the data and letting the data to speak. The idea of proposing this multivariate approach to measure selection bias and test balance comes from the consideration that in applied research all aspects of multivariate balance, not represented in the univariate variable- by-variable summaries, are ignored. The first part contains an introduction to evaluation methods as part of public and private decision process and a review of the literature of evaluation methods. The attention is focused on Rubin Potential Outcome Approach, matching methods, and briefly on Heckman’s Selection Model. The second part focuses on some resulting limitations of conventional methods, with particular attention to the problem of how testing in the correct way balancing. The third part contains the original contribution proposed , a simulation study that allows to check the performance of the method for a given dependence setting and an application to a real data set. Finally, we discuss, conclude and explain our future perspectives.

Satellite and in situ data integrated analysis to study the upper ocean an coastal environment of the Italian seas

The thesis objectives are to develop new methodologies for study of the space and time variability of Italian upper ocean ecosystem through the combined use of multi-sensors satellite data and in situ observations and to identify the capability and limits of remote sensing observations to monitor the marine state at short and long time scales. Three oceanographic basins have been selected and subjected to different types of analyses. The first region is the Tyrrhenian Sea where a comparative analysis of altimetry and lagrangian measurements was carried out to study the surface circulation. The results allowed to deepen the knowledge of the Tyrrhenian Sea surface dynamics and its variability and to defined the limitations of satellite altimetry measurements to detect small scale marine circulation features. Channel of Sicily study aimed to identify the spatial-temporal variability of phytoplankton biomass and to understand the impact of the upper ocean circulation on the marine ecosystem. An combined analysis of the satellite of long term time series of chlorophyll, Sea Surface Temperature and Sea Level field data was applied. The results allowed to identify the key role of the Atlantic water inflow in modulating the seasonal variability of the phytoplankton biomass in the region. Finally, Italian coastal marine system was studied with the objective to explore the potential capability of Ocean Color data in detecting chlorophyll trend in coastal areas. The most appropriated methodology to detect long term environmental changes was defined through intercomparison of chlorophyll trends detected by in situ and satellite. Then, Italian coastal areas subject to eutrophication problems were identified. This work has demonstrated that satellites data constitute an unique opportunity to define the features and forcing influencing the upper ocean ecosystems dynamics and can be used also to monitor environmental variables capable of influencing phytoplankton productivity.

"The capacity of contrastive analysis to successfully predict the errors of second language learners - a case study"

The aim of this dissertation is to show the power of contrastive analysis in successfully predicting the errors a language learner will make by means of a concrete case study. First, there is a description of what language transfer is and why it is important in the matter of second language acquisition. Second, a brief explanation of the history and development of contrastive analysis will be offered. Third, the focus of the thesis will move to an analysis of errors usually made by language learners. To conclude, the dissertation will focus on the concrete case study of a Russian learner of English: after an analysis of the errors the student is likely to make, a recorded conversation will be examined.